English

Adjacency matrices of random digraphs: singularity and anti-concentration

Probability 2016-10-19 v4 Combinatorics

Abstract

Let Dn,d{\mathcal D}_{n,d} be the set of all dd-regular directed graphs on nn vertices. Let GG be a graph chosen uniformly at random from Dn,d{\mathcal D}_{n,d} and MM be its adjacency matrix. We show that MM is invertible with probability at least 1Cln3d/d1-C\ln^{3} d/\sqrt{d} for Cdcn/ln2nC\leq d\leq cn/\ln^2 n, where c,Cc, C are positive absolute constants. To this end, we establish a few properties of dd-regular directed graphs. One of them, a Littlewood-Offord type anti-concentration property, is of independent interest. Let JJ be a subset of vertices of GG with Jn/d|J|\approx n/d. Let δi\delta_i be the indicator of the event that the vertex ii is connected to JJ and define δ=(δ1,δ2,...,δn){0,1}n\delta = (\delta_1, \delta_2, ..., \delta_n)\in \{0, 1\}^n. Then for every v{0,1}nv\in\{0,1\}^n the probability that δ=v\delta=v is exponentially small. This property holds even if a part of the graph is "frozen".

Keywords

Cite

@article{arxiv.1511.00113,
  title  = {Adjacency matrices of random digraphs: singularity and anti-concentration},
  author = {Alexander E. Litvak and Anna Lytova and Konstantin Tikhomirov and Nicole Tomczak-Jaegermann and Pierre Youssef},
  journal= {arXiv preprint arXiv:1511.00113},
  year   = {2016}
}

Comments

Final version

R2 v1 2026-06-22T11:33:44.098Z